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simmediumpolicy-learningmetric · varies
Rainbow-DemoRL: Combining Improvements in Demonstration-Augmented Reinforcement Learning
Description
Several approaches have been proposed to improve the sample efficiency of online reinforcement learning (RL) by leveraging demonstrations collected offline. The offline data can be used directly as transitions to optimize RL objectives, or offline policy and value functions can first be learned from the data and then used for online finetuning or to provide reference actions. While each of these strategies has shown compelling results, it is unclear which method has the most impact on sample eff